Results 61 to 70 of about 66,463 (260)
Advanced Intelligent Systems, EarlyView.This study introduces a data‐driven framework that combines deep reinforcement learning with classical path planning to achieve adaptive microrobot navigation. By training a surrogate neural network to emulate microrobot dynamics, the approach improves learning efficiency, reduces training time, and enables robust real‐time obstacle avoidance in ...
Amar Salehi +3 more
wiley +1 more source
First-Order Uncertain Hidden Semi-Markov Process for Failure Prognostics With Scarce Data
IEEE Access, 2020 Failure prognostics aims at predicting the object equipment's future degradation trend and derives the remaining useful life with a predefined failure threshold.
Jie Liu
doaj +1 more source
Structured Inference for Recurrent Hidden Semi-markov Model [PDF]
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018 Segmentation and labeling for high dimensional time series is an important yet challenging task in a number of applications, such as behavior understanding and medical diagnosis. Recent advances to model the nonlinear dynamics in such time series data, has suggested to involve recurrent neural networks into Hidden Markov Models.
Hao Liu +5 more
openaire +1 more source
Advanced Intelligent Systems, EarlyView.Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal +6 more
wiley +1 more source
IEEE Access, 2023 There is ongoing interest in the dynamics of resting state brain networks (RSNs) as potential predictors of cognitive and behavioural states. Multivariate Autoregressors (MAR) are used to model regional brain activity as a linear combination of past ...
Hernan Hernandez Larzabal +6 more
doaj +1 more source
Journal of Forecasting, EarlyView.ABSTRACT We study the accuracy of a variety of parametric price duration‐based realized variance estimators constructed via various financial duration models and compare their forecasting performance with the performance of various nonparametric return‐based realized variance estimators.
Björn Schulte‐Tillmann +2 more
wiley +1 more source
The Hierarchical Dirichlet Process Hidden Semi-Markov Model [PDF]
, 2010 There is much interest in the Hierarchical Dirichlet Process Hidden Markov Model (HDP-HMM) as a natural Bayesian nonparametric extension of the traditional HMM.
Johnson, Matthew James, Willsky, Alan S
core
Hidden Markov Quantile Models With Trends for Analysing Air Temperature Data
International Journal of Climatology, EarlyView.There is the question of whether climate change, expressed by time‐trends in temperature, is of a heterogeneous nature or not. Here, the time‐trend heterogeneity argument has been investigated using Hidden Markov (HM) quantile time‐trends models in temperature time series.
Georgios Tsiotas +2 more
wiley +1 more source
Sensors, 2019 Lower limb locomotion activity is of great interest in the field of human activity recognition. In this work, a triplet semi-Markov model-based method is proposed to recognize the locomotion activities of healthy individuals when lower limbs move ...
Haoyu Li +2 more
doaj +1 more source
Graphical models for social behavior modeling in face-to face interaction [PDF]
, 2016 International audienceThe goal of this paper is to model the coverbal behavior of a subject involved in face-to-face social interactions. For this end, we present a multimodal behavioral model based on a Dynamic Bayesian Network (DBN).
Bailly, Gérard +3 more
core +2 more sources